A density functional theory study on silver and bis-silver complexes with lighter tetrylene: are silver and bis-silver carbenes candidates for SARS-CoV-2 inhibition? Insight from molecular docking simulation

Polypropylene Modified with Ag-Based Semiconductors as a Potential Material against SARS-CoV-2 and Other Pathogens

The worldwide outbreak of the coronavirus pandemic (COVID-19) and other emerging infections are difficult and sometimes impossible to treat, making them one of the major public health problems of our time. It is noteworthy that Ag-based semiconductors can help orchestrate several strategies to fight this serious societal issue. In this work, we present the synthesis of α-Ag₂WO₄, β-Ag₂MoO₄, and Ag₂CrO₄ and their immobilization in polypropylene in the amounts of 0.5, 1.0, and 3.0 wt %, respectively. The antimicrobial activity of the composites was investigated against the Gram-negative bacterium Escherichia coli, the Gram-positive bacterium Staphylococcus aureus, and the fungus Candida albicans. The best antimicrobial efficiency was achieved by the composite with α-Ag₂WO₄, which completely eliminated the microorganisms in up to 4 h of exposure. The composites were also tested for the inhibition of SARS-CoV-2 virus, showing antiviral efficiency higher than 98% in just 10 min. Additionally, we evaluated the stability of the antimicrobial activity, resulting in constant inhibition, even after material aging. The antimicrobial activity of the compounds was attributed to the production of reactive oxygen species by the semiconductors, which can induce high local oxidative stress, causing the death of these microorganisms.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

In Silico Inhibitability of Copper Carbenes and Silylenes against Rhizoctonia solani and Magnaporthe oryzae

Copper lighter tetrylenes are promising for inhibition towards Rhizoctonia solani-based protein PDB-4G9M and Magnaporthe oryzae-based PDB-6JBR in rice. Quantum properties of four hypothetic copper complexes of carbenes and silylenes (Cu-NHC1, Cu-NHC2, Cu-NHSi1, and Cu-NHSi2) were examined using the density functional theory. Their inhibitability towards the targeted proteins was evaluated using molecular docking simulation. Quantum analysis predicts the stability of the investigated complexes and thus their practical existability and practicable synthesisability. Their electronic configurations are justified as highly conducive to intermolecular interaction. Regarding ligand-protein as carbenes/silylenes-4G9M inhibitory structures, the stability is estimated in the order [Cu-NHC2]-4G9M (DS −12.9 kcal⋅mol−1) > [Cu-NHSi1]-4G9M (DS −11.8 kcal⋅mol−1) = [Cu-NHSi2]-4G9M (DS −11.7 kcal⋅mol−1) > [Cu-NHC1]-4G9M (DS –11.4 kcal⋅mol−1). In contrast, the corresponding order for the carbenes/silylenes-6JBR systems is [Cu-NHSi2]-6JBR (DS –13.4 kcal⋅mol−1) > [Cu-NHC2]-6JBR (DS −13.0 kcal⋅mol−1) = [Cu-NHSi1]-6JBR (DS −12.6 kcal⋅mol−1) > [Cu-NHC1]-6JBR (DS −12.3 kcal⋅mol−1). In theory, this study suggests a potentiality of copper lighter tetrylenes and their derivatives against the infection of fungi Rhizoctonia solani and Magnaporthe oryzae, thus encouraging attempts for experimental developments.

Applications of density functional theory in COVID-19 drug modeling

The rapidly evolving Coronavirus 2019 (COVID-19) pandemic has led to millions of deaths around the world, highlighting the pressing need to develop effective antiviral pharmaceuticals. Recent efforts with computer-aided rational drug discovery have allowed detailed examination of drug–macromolecule interactions primarily by molecular mechanics (MM) techniques. Less widely applied in COVID-19 drug modeling is density functional theory (DFT), a quantum mechanics (QM) method that enables electronic structure calculations and elucidations of reaction mechanisms. Here, we review recent advances in applying DFT in molecular modeling studies of COVID-19 pharmaceuticals. We start by providing an overview of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) drugs and targets, followed by a brief introduction to DFT. We then provide a discussion of different approaches by which DFT has been applied. Finally, we discuss essential factors to consider when incorporating DFT in future drug modeling research.

On the Inhibitability of Natural Products Isolated from Tetradium ruticarpum towards Tyrosine Phosphatase 1B (PTP1B) and α-Glucosidase (3W37): An In Vitro and In Silico Study

Folk experiences suggest natural products in Tetradium ruticarpum can be effective inhibitors towards diabetes-related enzymes. The compounds were experimentally isolated, structurally elucidated, and tested in vitro for their inhibition effects on tyrosine phosphatase 1B (PTP1B) and α-glucosidase (3W37). Density functional theory and molecular docking techniques were utilized as computational methods to predict the stability of the ligands and simulate interaction between the studied inhibitory agents and the targeted proteins. Structural elucidation identifies two natural products: 2-heptyl-1-methylquinolin-4-one (1) and 3-[4-(4-methylhydroxy-2-butenyloxy)-phenyl]-2-propenol (2). In vitro study shows that the compounds (1 and 2) possess high potentiality for the inhibition of PTP1B (IC50 values of 24.3 ± 0.8, and 47.7 ± 1.1 μM) and α-glucosidase (IC50 values of 92.1 ± 0.8, and 167.4 ± 0.4 μM). DS values and the number of interactions obtained from docking simulation highly correlate with the experimental results yielded. Furthermore, in-depth analyses of the structure-activity relationship suggest significant contributions of amino acids Arg254 and Arg676 to the conformational distortion of PTP1B and 3W37 structures overall, thus leading to the deterioration of their enzymatic activity observed in assay-based experiments. This study encourages further investigations either to develop appropriate alternatives for diabetes treatment or to verify the role of amino acids Arg254 and Arg676.

O,N-Heterocyclic germylenes as efficient catalysts for hydroboration and cyanosilylation of benzaldehyde

Novel O,N-heterocyclic germylenes were examined as catalysts for cyanosilylation and hydroboration of benzaldehyde.